Analyzing-Spotify-and-YouTube-Songs-Using-Python-MySQL

BreadcrumbsAnalyzing - Spotify and YouTube Songs Using Python & MySQL

Description

BreadcrumbsAnalyzing is a Python-based project that analyzes Spotify and YouTube songs' data to provide insights into popular music trends. It uses the Spotify API and YouTube Data API to collect song information and stores it in a MySQL database for further analysis.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Data Sources
• Database Schema
• Contributing
• License
• Contact

Introduction

Music enthusiasts often wonder about the correlation between popular songs on Spotify and their performance on YouTube. This project aims to shed light on this relationship by fetching data from both platforms, aggregating it in a MySQL database, and performing data analysis to draw meaningful conclusions.

Features

• Fetches song data from the Spotify API and YouTube Data API.
• Stores the collected data in a MySQL database for persistence.
• Provides interactive data visualization to compare Spotify and YouTube song metrics.
• Performs statistical analysis to identify trends and patterns.
• Supports custom queries to extract specific insights from the data.

Installation

1. Clone the repository: git clone https://github.com/your-username/BreadcrumbsAnalyzing.git
2. Navigate to the project directory: cd BreadcrumbsAnalyzing
3. Install the required Python packages: pip install -r requirements.txt
4. Ensure you have a MySQL server running, and update the database configuration in config.py.

Usage

1. Run the data collection script to fetch song data:

   python fetch_data.py